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13 - Electrical and Electronic Engineering, Metallurgy and Materials

University of Sheffield : A - Electronic and Electrical Engineering

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Article title

An Overview and Performance Evaluation of Classification-Based Least Squares Trained Filters

Type

D - Journal article

DOI

10.1109/TIP.2008.2002162

Title of journal

IEEE Transactions on Image Processing

Article number

Volume number

Issue number

First page of article

1772

ISSN of journal

10577149

Year of publication

2008

URL

Number of additional authors

Additional information

Algorithm proposed for optimising filter coefficients based on an off-line training procedure and dedicated image content classification for various image restoration/enhancement applications, such as denoising, sharpening and resolution enhancement. The off-line training is efficient and the online filtering is real-time. The proposed 'Trained Filters' perform significantly better than many heuristically-designed filters. Algorithm has been implemented in ASIC for Philips high-definition TV sets (IhorKirenko: ihor.kirenko@philips.com) and in FPGA for BOSCH video surveillance cameras (SachaCvetković: sacha.cvetkovic@nl.bosch.com). Two EU patent applications (07300718.9, 06123138.7) have been filed. This also led to a PhD studentship funded by Bosch (JanKlijn: jan.klijn@nl.bosch.com).

Interdisciplinary

Cross-referral requested

Research group

None

Proposed double-weighted

Double-weighted statement

Reserve for a double-weighted output

Non-English

English abstract